OpenRaiser/Intern-Atlas huggingface dataset:
Flexible Lyapunov Functions and Applications to Fast Mechatronic Systems
Venue: arXiv cs.OH 2010
Year: 2010

The property that every control system should posses is stability, which translates into safety in real-life applications. A central tool in systems theory for synthesizing control laws that achieve stability are control Lyapunov functions (CLFs). Classically, a CLF enforces that the resulting closed-loop state trajectory is contained within a cone with a fixed, predefined shape, and which is centered at and converges to a desired converging point. However, such a requirement often proves to be overconservative, which is why most of the real-time controllers do not have a stability guarantee. Recently, a novel idea that improves the design of CLFs in terms of flexibility was proposed. The focus of this new approach is on the design of optimization problems that allow certain parameters that define a cone associated with a standard CLF to be decision variables. In this way non-monotonicity of the CLF is explicitly linked with a decision variable that can be optimized on-line. Conservativeness is significantly reduced compared to classical CLFs, which makes \emph{flexible CLFs} more suitable for stabilization of constrained discrete-time nonlinear systems and real-time control. The purpose of this overview is to highlight the potential of flexible CLFs for real-time control of fast mechatronic systems, with sampling periods below one millisecond, which are widely employed in aerospace and automotive applications.
On the Flow-level Dynamics of a Packet-switched Network
Venue: arXiv cs.NI 2010
Year: 2010

The packet is the fundamental unit of transportation in modern communication networks such as the Internet. Physical layer scheduling decisions are made at the level of packets, and packet-level models with exogenous arrival processes have long been employed to study network performance, as well as design scheduling policies that more efficiently utilize network resources. On the other hand, a user of the network is more concerned with end-to-end bandwidth, which is allocated through congestion control policies such as TCP. Utility-based flow-level models have played an important role in understanding congestion control protocols. In summary, these two classes of models have provided separate insights for flow-level and packet-level dynamics of a network.
Hybrid approach for Image Encryption Using SCAN Patterns and Carrier Images
Venue: arXiv cs.CR 2010
Year: 2010

We propose a hybrid technique for image encryption which employs the concept of carrier image and SCAN patterns generated by SCAN methodology. Although it involves existing method like SCAN methodology, the novelty of the work lies in hybridizing and carrier image creation for encryption. Here the carrier image is created with the help of alphanumeric keyword. Each alphanumeric key will be having a unique 8bit value generated by 4 out of 8-code. This newly generated carrier image is added with original image to obtain encrypted image. The scan methodology is applied to either original image or carrier image, after the addition of original image and carrier image to obtain highly distorted encrypted image. The resulting image is found to be more distorted in hybrid technique. By applying the reverse process we get the decrypted image.
On the Design of Efficient CSMA Algorithms for Wireless Networks
Venue: arXiv cs.NI 2010
Year: 2010

Recently, it has been shown that CSMA algorithms which use queue length-based link weights can achieve throughput optimality in wireless networks. In particular, a key result by Rajagopalan, Shah, and Shin (2009) shows that, if the link weights are chosen to be of the form log(log(q)) (where q is the queue-length), then throughput optimality is achieved. In this paper, we tighten their result by showing that throughput optimality is preserved even with weight functions of the form log(q)/g(q), where g(q) can be a function that increases arbitrarily slowly. The significance of the result is due to the fact that weight functions of the form log(q)/g(q) seem to achieve the best delay performance in practice.
Public-key cryptography in functional programming context
Venue: arXiv cs.CR 2010
Year: 2010

Up to now, for efficiency reasons cryptographic algorithm has been written in an imperative language. But to get acquaintance with a functional programming language a question arises: functional programming offers some new for secure communication or not? This article investigates this question giving an overview on some cryptography algorithms and presents how the RSA encryption in the functional language Clean can be implemented and how can be measured the efficiency of a certain application.
Automatic derivation of domain terms and concept location based on the analysis of the identifiers
Venue: arXiv cs.CL 2010
Year: 2010

Developers express the meaning of the domain ideas in specifically selected identifiers and comments that form the target implemented code. Software maintenance requires knowledge and understanding of the encoded ideas. This paper presents a way how to create automatically domain vocabulary. Knowledge of domain vocabulary supports the comprehension of a specific domain for later code maintenance or evolution. We present experiments conducted in two selected domains: application servers and web frameworks. Knowledge of domain terms enables easy localization of chunks of code that belong to a certain term. We consider these chunks of code as "concepts" and their placement in the code as "concept location". Application developers may also benefit from the obtained domain terms. These terms are parts of speech that characterize a certain concept. Concepts are encoded in "classes" (OO paradigm) and the obtained vocabulary of terms supports the selection and the comprehension of the class' appropriate identifiers. We measured the following software products with our tool: JBoss, JOnAS, GlassFish, Tapestry, Google Web Toolkit and Echo2.
Polar Coding for Secure Transmission and Key Agreement
Venue: arXiv cs.IT 2010
Year: 2010

Wyner's work on wiretap channels and the recent works on information theoretic security are based on random codes. Achieving information theoretical security with practical coding schemes is of definite interest. In this note, the attempt is to overcome this elusive task by employing the polar coding technique of Arıkan. It is shown that polar codes achieve non-trivial perfect secrecy rates for binary-input degraded wiretap channels while enjoying their low encoding-decoding complexity. In the special case of symmetric main and eavesdropper channels, this coding technique achieves the secrecy capacity. Next, fading erasure wiretap channels are considered and a secret key agreement scheme is proposed, which requires only the statistical knowledge of the eavesdropper channel state information (CSI). The enabling factor is the creation of advantage over Eve, by blindly using the proposed scheme over each fading block, which is then exploited with privacy amplification techniques to generate secret keys.
Randomly removing g handles at once
Venue: arXiv cs.CG 2010
Year: 2010

Indyk and Sidiropoulos (2007) proved that any orientable graph of genus $g$ can be probabilistically embedded into a graph of genus $g-1$ with constant distortion. Viewing a graph of genus $g$ as embedded on the surface of a sphere with $g$ handles attached, Indyk and Sidiropoulos' method gives an embedding into a distribution over planar graphs with distortion $2^{O(g)}$, by iteratively removing the handles. By removing all $g$ handles at once, we present a probabilistic embedding with distortion $O(g^2)$ for both orientable and non-orientable graphs. Our result is obtained by showing that the nimum-cut graph of Erickson and Har Peled (2004) has low dilation, and then randomly cutting this graph out of the surface using the Peeling Lemma of Lee and Sidiropoulos (2009).
Analysis, Modification, and Implementation (AMI) of Scheduling Algorithm for the IEEE 802.116e (Mobile WiMAX)
Venue: arXiv cs.NI 2010
Year: 2010

Mobile WiMAX (Worldwide Interoperability for Microwave Access) is being touted as the most promising and potential broadband wireless technology. And the popularity rate has been surging to newer heights as the knowledge-backed service era unfolds steadily. Especially Mobile WiMAX is being projected as a real and strategic boon for developing counties such as India due to its wireless coverage acreage is phenomenally high. Mobile WiMAX has spurred tremendous interest from operators seeking to deploy high-performance yet cost-effective broadband wireless networks. The IEEE 802.16e standard based Mobile WiMAX system will be investigated for the purpose of Quality of Service provisioning. As a technical challenge, radio resource management will be primarily considered and main is the costly spectrum and the increasingly more demanding applications with ever growing number of subscribers. It is necessary to provide Quality of Service (QoS) guaranteed with different characteristics. As a possible solution the scheduling algorithms will be taken into main consideration and the present well known algorithms will be described. In this paper, we have highlighted the following critical issues for Mobile WiMAX technologies. This paper specifically discussed about the below mentioned in detail. - QoS Requirements For IEEE 802.16 Service Classes, Achieving efficient radio resource management. - Deficit Round Robin (DRR) Scheduling algorithm. - Modified Deficit Round Robin (MDRR) scheduling algorithm's attributes, properties and architecture. System Model And Scenarios Using OPNET Modeler Software. - Simulation Limitations And Constraints.
Hierarchical Web Page Classification Based on a Topic Model and Neighboring Pages Integration
Venue: arXiv cs.LG 2010
Year: 2010

Most Web page classification models typically apply the bag of words (BOW) model to represent the feature space. The original BOW representation, however, is unable to recognize semantic relationships between terms. One possible solution is to apply the topic model approach based on the Latent Dirichlet Allocation algorithm to cluster the term features into a set of latent topics. Terms assigned into the same topic are semantically related. In this paper, we propose a novel hierarchical classification method based on a topic model and by integrating additional term features from neighboring pages. Our hierarchical classification method consists of two phases: (1) feature representation by using a topic model and integrating neighboring pages, and (2) hierarchical Support Vector Machines (SVM) classification model constructed from a confusion matrix. From the experimental results, the approach of using the proposed hierarchical SVM model by integrating current page with neighboring pages via the topic model yielded the best performance with the accuracy equal to 90.33% and the F1 measure of 90.14%; an improvement of 5.12% and 5.13% over the original SVM model, respectively.
Clinical gait data analysis based on Spatio-Temporal features
Venue: arXiv cs.CV 2010
Year: 2010

Analysing human gait has found considerable interest in recent computer vision research. So far, however, contributions to this topic exclusively dealt with the tasks of person identification or activity recognition. In this paper, we consider a different application for gait analysis and examine its use as a means of deducing the physical well-being of people. The proposed method is based on transforming the joint motion trajectories using wavelets to extract spatio-temporal features which are then fed as input to a vector quantiser; a self-organising map for classification of walking patterns of individuals with and without pathology. We show that our proposed algorithm is successful in extracting features that successfully discriminate between individuals with and without locomotion impairment.
Constrained Non-Monotone Submodular Maximization: Offline and Secretary Algorithms
Venue: arXiv cs.DS 2010
Year: 2010

Constrained submodular maximization problems have long been studied, with near-optimal results known under a variety of constraints when the submodular function is monotone. The case of non-monotone submodular maximization is less understood: the first approximation algorithms even for the unconstrainted setting were given by Feige et al. (FOCS '07). More recently, Lee et al. (STOC '09, APPROX '09) show how to approximately maximize non-monotone submodular functions when the constraints are given by the intersection of p matroid constraints; their algorithm is based on local-search procedures that consider p-swaps, and hence the running time may be n^Omega(p), implying their algorithm is polynomial-time only for constantly many matroids. In this paper, we give algorithms that work for p-independence systems (which generalize constraints given by the intersection of p matroids), where the running time is poly(n,p). Our algorithm essentially reduces the non-monotone maximization problem to multiple runs of the greedy algorithm previously used in the monotone case. Our idea of using existing algorithms for monotone functions to solve the non-monotone case also works for maximizing a submodular function with respect to a knapsack constraint: we get a simple greedy-based constant-factor approximation for this problem. With these simpler algorithms, we are able to adapt our approach to constrained non-monotone submodular maximization to the (online) secretary setting, where elements arrive one at a time in random order, and the algorithm must make irrevocable decisions about whether or not to select each element as it arrives. We give constant approximations in this secretary setting when the algorithm is constrained subject to a uniform matroid or a partition matroid, and give an O(log k) approximation when it is constrained by a general matroid of rank k.
A multivalued knowledge-base model
Venue: arXiv cs.AI 2010
Year: 2010

The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these ideas the concept of multivalued knowledge-base will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At last a possible evaluation strategy is given.
Content based Zero-Watermarking Algorithm for Authentication of Text Documents
Venue: arXiv cs.CR 2010
Year: 2010

Copyright protection and authentication of digital contents has become a significant issue in the current digital epoch with efficient communication mediums such as internet. Plain text is the rampantly used medium used over the internet for information exchange and it is very crucial to verify the authenticity of information. There are very limited techniques available for plain text watermarking and authentication. This paper presents a novel zero-watermarking algorithm for authentication of plain text. The algorithm generates a watermark based on the text contents and this watermark can later be extracted using extraction algorithm to prove the authenticity of text document. Experimental results demonstrate the effectiveness of the algorithm against tampering attacks identifying watermark accuracy and distortion rate on 10 different text samples of varying length and attacks.
Knowledge Management
Venue: arXiv cs.OH 2010
Year: 2010

This paper discusses the important process of knowledge and its management, and differences between tacit and explicit knowledge and understanding the culture as a key issue for the successful implementation of knowledge management, in addition to, this paper is concerned with the four-stage model for the evolution of information technology (IT) support for knowledge management in law firms.
Facial Gesture Recognition Using Correlation And Mahalanobis Distance
Venue: arXiv cs.CV 2010
Year: 2010

Augmenting human computer interaction with automated analysis and synthesis of facial expressions is a goal towards which much research effort has been devoted recently. Facial gesture recognition is one of the important component of natural human-machine interfaces; it may also be used in behavioural science, security systems and in clinical practice. Although humans recognise facial expressions virtually without effort or delay, reliable expression recognition by machine is still a challenge. The face expression recognition problem is challenging because different individuals display the same expression differently. This paper presents an overview of gesture recognition in real time using the concepts of correlation and Mahalanobis distance.We consider the six universal emotional categories namely joy, anger, fear, disgust, sadness and surprise.
A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron
Venue: arXiv cs.CV 2010
Year: 2010

The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The seven feature sets employed here consist of shadow features, octant centroids, longest runs, angular distances, effective spans, dynamic centers of gravity, and some of their combinations. On experimentation with a database of 3000 samples, the maximum recognition rate of 95.80% is observed with both of two separate combinations of features. One of these combinations consists of shadow and centriod features, i. e. 88 features in all, and the other shadow, centroid and longest run features, i. e. 124 features in all. Out of these two, the former combination having a smaller number of features is finally considered effective for applications related to Optical Character Recognition (OCR) of handwritten Arabic numerals. The work can also be extended to include OCR of handwritten characters of Arabic alphabet.
Distributed Principal Component Analysis for Wireless Sensor Networks
Venue: arXiv cs.NI 2010
Year: 2010

The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements are projected on a set of principal components. When sensor measurements are correlated, a small set of principal components can explain most of the measurements variability. This allows to significantly decrease the amount of radio communication and of energy consumption. In this paper, we show that the power iteration method can be distributed in a sensor network in order to compute an approximation of the principal components. The proposed implementation relies on an aggregation service, which has recently been shown to provide a suitable framework for distributing the computation of a linear transform within a sensor network. We also extend this previous work by providing a detailed analysis of the computational, memory, and communication costs involved. A compression experiment involving real data validates the algorithm and illustrates the tradeoffs between accuracy and communication costs.
Quantifying Shannon's Work Function for Cryptanalytic Attacks
Venue: arXiv cs.CR 2010
Year: 2010

Attacks on cryptographic systems are limited by the available computational resources. A theoretical understanding of these resource limitations is needed to evaluate the security of cryptographic primitives and procedures. This study uses an Attacker versus Environment game formalism based on computability logic to quantify Shannon's work function and evaluate resource use in cryptanalysis. A simple cost function is defined which allows to quantify a wide range of theoretical and real computational resources. With this approach the use of custom hardware, e.g., FPGA boards, in cryptanalysis can be analyzed. Applied to real cryptanalytic problems, it raises, for instance, the expectation that the computer time needed to break some simple 90 bit strong cryptographic primitives might theoretically be less than two years.
Interference Focusing for Mitigating Cross-Phase Modulation in a Simplified Optical Fiber Model
Venue: arXiv cs.IT 2010
Year: 2010

A memoryless interference network model is introduced that is based on non-linear phenomena observed when transmitting information over optical fiber using wavelength division multiplexing. The main characteristic of the model is that amplitude variations on one carrier wave are converted to phase variations on another carrier wave, i.e., the carriers interfere with each other through amplitude-to-phase conversion. For the case of two carriers, a new technique called interference focusing is proposed where each carrier achieves the capacity pre-log 1, thereby doubling the pre-log of 1/2 achieved by using conventional methods. The technique requires neither channel time variations nor global channel state information. Generalizations to more than two carriers are outlined.
On Ergodic Secrecy Capacity for Gaussian MISO Wiretap Channels
Venue: arXiv cs.IT 2010
Year: 2010

A Gaussian multiple-input single-output (MISO) wiretap channel model is considered, where there exists a transmitter equipped with multiple antennas, a legitimate receiver and an eavesdropper each equipped with a single antenna. We study the problem of finding the optimal input covariance that achieves ergodic secrecy capacity subject to a power constraint where only statistical information about the eavesdropper channel is available at the transmitter. This is a non-convex optimization problem that is in general difficult to solve. Existing results address the case in which the eavesdropper or/and legitimate channels have independent and identically distributed Gaussian entries with zero-mean and unit-variance, i.e., the channels have trivial covariances. This paper addresses the general case where eavesdropper and legitimate channels have nontrivial covariances. A set of equations describing the optimal input covariance matrix are proposed along with an algorithm to obtain the solution. Based on this framework, we show that when full information on the legitimate channel is available to the transmitter, the optimal input covariance has always rank one. We also show that when only statistical information on the legitimate channel is available to the transmitter, the legitimate channel has some general non-trivial covariance, and the eavesdropper channel has trivial covariance, the optimal input covariance has the same eigenvectors as the legitimate channel covariance. Numerical results are presented to illustrate the algorithm.
Up-sampling and Natural Sample Value Computation for Digital Pulse Width Modulators
Venue: arXiv cs.SD 2010
Year: 2010

Digital pulse width modulation has been considered for high-fidelity and high-efficiency audio amplifiers for several years. It has been shown that the distortion can be reduced and the implementation of the system can be simplified if the switching frequency is much higher than the Nyquist rate of the modulating waveform. Hence, the input digital source is normally upsampled to a higher frequency. It was also proved that converting uniform samples to natural samples will decrease the harmonic distortion. Thus, in this paper, we examine a new approach that combines upsampling, digital interpolation and natural sampling conversion. This approach uses poly-phase implementation of the digital interpolation filter and digital differentiators. We will show that the structure consists of an FIR-type linear stage and a nonlinear stage. Some spectral simulation results of a pulse width modulation system based on this approach will also be presented. Finally, we will discuss the improvement of the new approach over old algorithms.